Search results for "Vector"

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

2016

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new…

Targeting Homer genes using adeno-associated viral vector: lessons learned from behavioural and neurochemical studies.

2008

Over a decade of in-vitro data support a critical role for members of the Homer family of postsynaptic scaffolding proteins in regulating the functional architecture of glutamate synapses. Earlier studies of Homer knockout mice indicated a necessary role for Homer gene products in normal mesocorticolimbic glutamate transmission and behaviours associated therewith. The advent of adeno-associated viral vectors carrying cDNA for, or short hairpin RNA against, specific Homer isoforms enabled the site-directed targeting of Homers to neurons in the brain. This approach has allowed our groups to address developmental issues associated with conventional knockout mice, to confirm active roles for di…

SVG Rendering by Watershed Decomposition

2005

THE OPTIMAL SCALING OF A LINEAR RELUCTANCE MOTOR BY FIELD COMPUTATION

1995

The work aims at investigating the law of miniaturization of a linear reluctance motor by expressing the ratio of force to mass as a function of bar position in per unit, for different scale factors. Corresponding to the same factors, inductance is also computed. Finally the ratio of the bar length to external diameter is changed and the analysis is accordingly repeated.

Thermodynamics of a small system in a μT reservoir

2011

Abstract Due to advances in experimental techniques operating at the nanoscale, it is possible to compute properties from density fluctuations by studying ‘snapshots’ of particle configurations. Thermodynamics on a small scale is different from thermodynamics in bulk systems. We show how the molar enthalpy h and the inverse thermodynamic correction factor Γ - 1 depend on system size and how these properties can be computed from fluctuations at the nanoscale. We find a 1/ L finite size effect for all thermodynamic quantities for a small system in contact with a reservoir, where L is the length of the system in a single dimension.

Experimental and Modeling Analyses of Human Motion Across the Static Magnetic Field of an MRI Scanner

2021

It is established that human movements in the vicinity of a permanent static magnetic field, such as those in magnetic resonance imaging (MRI) scanners induce electric fields in the human body; this raises potential severe risks of health to radiographers and cleaners exposed routinely to these fields in MRI rooms. The relevant directives and parameters, however, are based on theoretical models, and accurate studies on the simulation of the effects based on human movement data obtained in real conditions are still lacking. Two radiographers and one cleaner, familiar with MRI room activities and these directives, were gait analyzed during the execution of routine job motor tasks at different…

The role of vector-baryon channels and resonances in the γp→K0Σ+ and γn→K0Σ0 reactions near the K⁎Λ threshold

2013

Abstract We have studied the γ p → K 0 Σ + reaction in the energy region around the K ⁎ Λ and K ⁎ Σ thresholds, where the CBELSA/TAPS cross section shows a sudden drop and the differential cross section experiences a transition from a forward-peaked distribution to a flat one. Our coupled-channel model incorporates the dynamics of the vector meson–baryon interaction which is obtained from the hidden gauge formalism. We find that the cross section in this energy region results from a delicate interference between amplitudes having K ⁎ Λ and K ⁎ Σ intermediate states. The sharp downfall is dictated by the presence of a nearby N ⁎ resonance produced by our model, a feature that we have employe…

Regge phenomenology in π0 and η photoproduction

2017

The $\ensuremath{\gamma}N\ensuremath{\rightarrow}{\ensuremath{\pi}}^{0}N$ and $\ensuremath{\gamma}N\ensuremath{\rightarrow}\ensuremath{\eta}N$ reactions at photon beam energies above 4 GeV are investigated within Regge models. The models include $t$-channel exchanges of vector ($\ensuremath{\rho}$ and $\ensuremath{\omega}$) and axial-vector (${b}_{1}$ and ${h}_{1}$) mesons. Moreover, Regge cuts of $\ensuremath{\rho}\mathbb{P},\phantom{\rule{0.28em}{0ex}}\ensuremath{\rho}{f}_{2},\phantom{\rule{0.28em}{0ex}}\ensuremath{\omega}\mathbb{P}$, and $\ensuremath{\omega}{f}_{2}$ are investigated. A good description of differential cross sections and polarization observables at photon beam energies fr…

On Obtaining Classification Confidence, Ranked Predictions and AUC with Tsetlin Machines

2020

Tsetlin machines (TMs) are a promising approach to machine learning that uses Tsetlin Automata to produce patterns in propositional logic, leading to binary (hard) classifications. In many applications, however, one needs to know the confidence of classifications, e.g. to facilitate risk management. In this paper, we propose a novel scheme for measuring TM confidence based on the logistic function, calculated from the propositional logic patterns that match the input. We then use this scheme to trade off precision against recall, producing area under receiver operating characteristic curves (AUC) for TMs. Empirically, using four real-world datasets, we show that AUC is a more sensitive meas…

A General Frame for Building Optimal Multiple SVM Kernels

2012

The aim of this paper is to define a general frame for building optimal multiple SVM kernels. Our scheme follows 5 steps: formal representation of the multiple kernels, structural representation, choice of genetic algorithm, SVM algorithm, and model evaluation. The computation of the optimal parameter values of SVM kernels is performed using an evolutionary method based on the SVM algorithm for evaluation of the quality of chromosomes. After the multiple kernel is found by the genetic algorithm we apply cross validation method for estimating the performance of our predictive model. We implemented and compared many hybrid methods derived from this scheme. Improved co-mutation operators are u…